On universal hypotheses testing via large deviations

A prototype problem in hypotheses testing is discussed. The problem of deciding whether an i.i.d. sequence of random variables has originated from a known source P₁ or an unknown source P₂ is considered. The exponential rate of decrease in type II probability of error under a constraint on the minimal rate of decrease in type I probability of error is chosen for a criterion of optimality. Using large deviations estimates, a decision rule that is based on the relative entropy of the empirical measure with respect to P₁ is proposed. In the case of discrete random variables, this approach yields weaker results than the combinatorial approach used by Hoeffding (1965). However, it enables the analysis to be extended to the general case of Rⁿ-valued random variables. Finally, the results are extended to the case where P₁ is an unknown parameter-dependent distribution that is known to belong to a set of distributions (P⁰₁, &thetas;∈Θ)     

Viscosity of a CaO-MgO-Al2O3-SiO2 melt containing spinel particles at 1646K

This article reports an experimental investigation into the effect of solid suspension on the viscosity of molten slags. Up to about 20 vol pct of spinel (MgAl₂O₄) particles of three size ranges (fine: 0.10 to 0.21 mm; medium: 0.21 to 0.44 mm; and coarse: 0.44 to 0.99 mm) were added to a CaO-MgO-Al₂O₃-SiO₂ melt at 1646 (±10)K. A Brookfield DVII+ viscometer was used. The viscosity determined for the solid-free melts was in good agreement with the results of published work. The viscosity for the solid-containing melt was found to increase with the addition of the particles. With more than 10 vol pct solid particles, particularly the fine and the coarse ones, the melt showed an apparent “Bingham” behavior, i.e., the shear stress increased linearly with the shear rate but had a residual shear stress (up to 3 Pa depending on the amount and size of solid added) at zero shear rate. The viscosity of the solid-containing slag, η, was found to fit an Einstein-Roscoe type equation, η=η ₀ (1−af)⁻ⁿ, where η ₀ is the viscosity of the solid-free melt, f is the volume fraction of solid particles in the melt, and a and n are parameters taking the value of 4.24, 3.29, and 3.56 and 1.28, 2.36, and 2.24 for the fine, medium, and coarse particles, respectively, for best fit.     

A new fretting fatigue testing machine design,utilizing rotating–bending principle approach

Fretting fatigue is a phenomenon which occurs when two parts are contacted to each other and one of those parts or both are subjected to cyclic load. Fretting decreases fatigue life of materials drastically by half or even more. Therefore, investigation of fretting fatigue life of materials is an important subject. Fretting fatigue tests are usually performed using universal hydraulic testing devices. In this work, a rotating bending apparatus for fretting fatigue test is introduced in which the cyclic load is provided by an adjustable eccentric load. The apparatus called RBFF machine which is the abbreviation of rotating bending fretting fatigue. The eccentric load is measured by load cell. The coefficient of friction and fretting load are measured by foil strain gauges using a Wheatstone bridge configuration. The performance of the machine is verified with doing a comparison between fatigue lives of a number of AL7075-T6 alloy samples on a Shimadzu rotating bending fatigue testing machine and RBFF. The results shows very close assent between the operations of the two testing rigs. The main privileges of RBFF are its simplicity with respect to universal devices, cheapness and, coefficient of friction (between pads and specimen) evaluation during the test. The RBFF also has the capability of being used for any other soft and hard metals. It can be advanced further for high and low temperature.     

Fault diagnosis and classification based on wavelet transform and neural network

In this paper we present a novel method in fault recognition and classification in Nuclear Power Plant (NPP) using wavelet transform based Artificial Neural Network (ANN). We first simulate 10 design basis accidents (DBA) of a VVER-1000 using 15 input parameters with employing a Multilayer Perceptron (MLP) Neural Network with Resilient Backpropagation (RBP) algorithm. Afterwards we present the application of wavelet transform for its temporal shift property and multiresolution analysis characteristics to reduce disturbing perturbations in input training set data. Simulation of Artificial Neural Network and wavelet transform was performed using MATLAB software. The results show an enhanced accuracy and speed in fault recognition and high degree of robustness.     

Light‐Activated Reversible Imine Isomerization: Towards a Photochromic Protein Switch

Mutants of cellular retinoic acid‐binding protein II (CRABPII), engineered to bind all‐trans‐retinal as an iminium species, demonstrate photochromism upon irradiation with light at different wavelengths. UV light irradiation populates the cis‐imine geometry, which has a high pK_a, leading to protonation of the imine and subsequent “turn‐on” of color. Yellow light irradiation yields the trans‐imine isomer, which has a depressed pK_a, leading to loss of color because the imine is not protonated. The protein‐bound retinylidene chromophore undergoes photoinduced reversible interconversion between the colored and uncolored species, with excellent fatigue resistance.     

Vision-based quantitative assessment of microcracks on reactor internal components of nuclear power plants

Ageing power facilities are increasingly susceptible to the onset of damage related to long exposure to stress, radiation, elevated temperatures and environmental conditions. One failure mechanism of particular concern is the onset of stress corrosion cracking. Currently, a technician manually measures the crack thicknesses at few points along a microcrack in a microscopic image, and the results are quantified by the Root Mean Square (RMS) of these measurements. This approach is time-consuming and subjective. In addition, the crack thickness is an important but difficult characteristic to accurately describe in a single numerical value, since it can vary considerably along the length of a crack. In this paper, a vision-based methodology is proposed for accurate quantification of microcracks that provides the thickness measurements for each pixel along the crack centreline. The proposed approach provides the minimum, maximum, mean, standard deviation, RMS and the histogram of crack thicknesses, which in most cases yields thousands of measurements. This approach provides more comprehensive insight regarding the condition of a microcrack. A region-growing method is used for segmenting microcracks from complex backgrounds. The microcrack thicknesses are then automatically computed along the lines orthogonal to the crack centreline. The fast marching method is used to accurately estimate the centreline of microcracks. Several real microcracks are examined to evaluate the performance of the proposed methodology.     

An Agile Adaptive Clustering Algorithm for Wireless Sensor Networks Considering Energy Constraint

Wireless Personal Communications - Security in vehicular ad hoc network (VANET) is one of the major challenging topics and the secure key interchange between two legitimate vehicles is an important...     

Assessing the energy and greenhouse gas footprints of nickel laterite processing

The energy and greenhouse gas footprints of some of the various technologies that are used for processing nickel laterite ores have been assessed using life cycle assessment methodology based largely on publicly reported inventory data. The results of the study were used to identify opportunities to improve the energy and greenhouse gas impacts of the various processes and to examine how they might be affected under different future scenarios such as falling laterite ore grades and the possible imposition of a carbon tax. The opportunities identified included the use of biochar as a fuel and reductant, along with slag waste heat recovery in ferronickel smelting, and the use of the emerging bath smelting technology for ferronickel production instead of the rotary kiln/electric furnace process. As a significant amount of the life cycle-based greenhouse gas emissions from the hydrometallurgical acid leaching processes are generated by acid neutralisation with lime or limestone, there may be opportunities to reduce these emissions by utilising other neutralising agents or possibly by considering non-acid leaching systems. Improving the energy efficiency of the electrowinning stage used to recovery nickel metal from the leach liquor is another possible way in which the sustainability of hydrometallurgical production of nickel from laterite ores could be improved.